GPKB

GPKB integrates and manages heterogeneous genomic and proteomic annotations from sources such as Entrez Gene, UniProt, IntAct, Expasy Enzyme, GO, GOA, BioCyc, KEGG, Reactome and OMIM to provide a consolidated knowledge base for integrative functional annotation and ontology-driven inference.


Key Features:

  • Integration of Multiple Sources: Consolidates annotations from Entrez Gene, UniProt, IntAct, Expasy Enzyme, GO, GOA, BioCyc, KEGG, Reactome and OMIM to create a comprehensive view of genomic and proteomic data.
  • Flexible Architecture: Employs a flexible, modular, multilevel global data schema (built on the Genomic and Proteomic Data Warehouse, GPDW) that abstracts and generalizes integrated data features to accommodate changes in source content, structure, and number.
  • Automated Data Integration and Maintenance: Implements automatic procedures for data integration and maintenance that ensure data consistency, quality control, and provenance tracking as source databases evolve.
  • Semantic Closure and Ontology Management: Performs semantic closure on hierarchical relationships within integrated biomedical ontologies (e.g., GO, GOA) to enhance ontology coherence and support ontology-based inference.

Scientific Applications:

  • Integrative Annotation Aggregation: Aggregates gene and protein annotations across multiple databases to support comprehensive functional annotation.
  • Pathway and Disease Association Mapping: Maps genes and proteins to pathways and disease associations using KEGG, Reactome and OMIM.
  • Ontology-driven Knowledge Extraction: Enables ontology-driven inference and biomedical knowledge extraction through semantic closure of integrated ontologies.

Methodology:

Built on the Genomic and Proteomic Data Warehouse (GPDW), GPKB uses a multilevel global data schema to abstract integrated data features, automatic procedures for data integration, maintenance, consistency, quality and provenance tracking, and performs semantic closure on hierarchical relationships within integrated biomedical ontologies.

Topics

Details

Tool Type:
web application
Added:
11/17/2023
Last Updated:
12/16/2023

Operations

Publications

Masseroli M, Canakoglu A, Ceri S. Integration and Querying of Genomic and Proteomic Semantic Annotations for Biomedical Knowledge Extraction. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2016;13(2):209-219. doi:10.1109/tcbb.2015.2453944.

Masseroli M, Canakoglu A, Quigliatti M. Detection of gene annotations and protein-protein interaction associated disorders through transitive relationships between integrated annotations. BMC Genomics. 2015;16(S6). doi:10.1186/1471-2164-16-s6-s5. PMID:26046679. PMCID:PMC4460591.

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